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Why Do You Need a Recommender System for Your Online Business? 16 August 2021


Today we are so accustomed to getting recommended for desired commodities and services on the web that the buying experience has started to seem incomplete without it. Abundant alternatives available on the internet have compelled online businesses to come up with a personalized browsing environment with user-specific recommendations. That’s where conveniently, the role of the recommendation engine comes into play. More than conversion, the goal has now become engaging the users.


The jam experiment:

In 2000, Columbia and Stanford University psychologists conducted the following experiment. On the first day, customers of a local grocery store were presented with a sampling table with 24 varieties of Jam. A few days later, the same table had only six types of Jam. The goal was to judge which table would convert into more sales. The widespread assumption is that a greater variety of jams would attract more people and generate more revenue. However, it was observed that although the table with 24 jams developed more interest among consumers, it converted into fewer sales ( 10 times lower) than the table with six jams. So what happened here is that although a wide variety of choices does seem attractive to consumers, there may be an information overload that often confuses consumers. So despite the access to millions of items that online platforms have, these choices can harm the business without relevant recommendations. 


The recent digitalization of business has made the online environment far more competitive. Online retailers rely significantly on competitive advantages, including providing their clients with a more personalized experience. To achieve this, it is imperative to know each individual user and learn their consumption habits. With a vast number of products and services, a growing population of E-commerce users, and constantly changing buying habits, preparing and providing a personalized experience to each consumer manually is an uphill task. So, an AI-based recommender system is your answer. Following are a few of the reasons why it is necessary –


1. Creating Value for a Business:  

Recommender systems provide immense value to users as well as service providers. They reduce the overall transaction costs of browsing through and selecting products/services in an E-commerce setting. Recommender systems have also been proved to refine the decision-making process. A recommendation engine assures high returns in the SaaS industry because they increase your products’ visibility, ensure more engagement, and maximize conversion probability. In scientific libraries, these systems assist users by enabling them to access data further than catalog searches. Hence, the importance of incorporating effective and accurate recommendation procedures within a system for users cannot be stressed enough. What makes them even more useful are the several smart decisions taken by the recommender system every millisecond. Moreover, customized newsletters, personalized promotion content, and sending push notifications urge consumers to return to the site, increasing their frequency, reducing their churn rate, and ultimately generating long-term profits.



2. Increases Traffic

A recommender system potentially drives more traffic to your site using personalized notifications and emails, allowing repeat visits.


3. Delivers Relevant Content

A recommendation engine provides relevant product recommendations as to the consumer browses. The information is collected in real-time using usage patterns and browsing history, allowing the software to adjust to changing shopping patterns.


4. Increases Average Order Value and Number Of Items Per Order 

The average value of orders tends to increase when recommender systems are employed. The number of items per order also usually rises because when a consumer is shown options that meet their interest, they are more likely to add additional items to their order.


5. Generates Reports

The Generation and provision of consumer data reports is an integral part of a recommender system. Giving the client accurately and real-time information and figures allows them to make calculated decisions about his site and the direction of a campaign.


6. Offers Advice and Direction 

An experienced service provider can provide useful guidance on effectively using the information collected and reported to the client to their benefit. Acting as their colleague and, at times, their consultant, the client will have the necessary information to help guide the E-commerce platform to become more successful in the long run.


To know more about AI-based recommender systems, try the 14-day free trial of Alie.

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Kritika Verma is an Associate Content Writer and works with Muvi Marketing Team. She is an inbound marketing professional and ensures high-quality traffic on the Muvi website through her blogs, articles, and more. She has an engineering background but always had a knack for writing. In her free time, she is either on Quora or on (Mostly losing).

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